Polysubstance use, treatment completion, and contact with the justice system: a multistate analysis of treatments for substance use disorders between 2010-2019 in Chile

A. González-Santa Cruz1, 2, , J. Ruiz-Tagle Maturana1, 3, , M. Mateo Piñones1, 4, , A. Castillo-Carniglia5,


1 Young Researcher, Millennium Nucleus for the evaluation and analysis of Drug Policies
2 Ph.D. student, School of Public Health, Universidad de Chile
3 Ph.D. student, Programa de Doctorado en Políticas Públicas, Universidad Mayor, Santiago, Chile.
4 Ph.D. student, Griffith University, Australia
5 Director, Millennium Nucleus for the evaluation and analysis of Drug Policies; Associate Professor, Society & Health Research Center

Background

  • Substance use disorders (SUD) often co-occur with criminality, including violence, arrests, and incarceration\(^{[1; 2; 3]}\)

  • People with PSU has shown more contacts with the CJS than people with single substance use\(^{[4; 5; 6]}\).

  • The relationship between polysubstance use (PSU), treatment outcomes, and contact with the criminal justice system (CJS) is complex and not fully understood.

  • Completing SUD treatment can help to reduce the risk of contacts with the CJS, but it is not quite clear in people with PSU\(^{[7; 8; 9; 10; 11; 12]}\).

  • More research is needed to understand the link between PSU, treatment completion, and contact with the CJS, particularly in Latin America\(^{[13; 14; 15]}\).

  • Effective interventions and tailored approaches for people with PSU can help to mitigate the harms of SUDs and contact with the CJS

Objectives: Estimate the effects of PSU at baseline (vs. single substance use) on the probabilities of (i) completing baseline drug treatment and (ii) contacting with the CJS after treatment at 6 months, 1-, 3- & 5-years follow-ups.

Methods

Design: a retrospective cohort based on the administrative data’s record linkage. Data: Chilean substance use treatment programs and Prosecutor’s Office through a deterministic linkage process. Ethics: We are updating an existing ethical approval by the Griffith University Human Research Ethics Committee GUHREC, GU Ref No: 2022/919.

Variables

Exposure: baseline PSU (using more than one main substance among alcohol and illicit drugs at admission to SUD treatment); Mediator: SUD treatment outcome (complete vs. dropout or spelled by misconduct); Outcome: contact with CJS (committing an offense that led to a condemnatory sentence).

Analytical Plan

  • The research will control for a number of confounding variables (listed in Figure 1), and patients will be weighted by the inverse probability of PSU (IPW)\(^{[16]}\).

  • We described the cumulative incidence rate (x1,000 person-years) of patients with PSU and no PSU, and incidence rate ratios (IRR) of treatment completion and contact with CJS, with and without weighting for IPWs.

    Covariate balance

    Figure 1: Covariate balance

  • We used an illness-death multistate structure to estimate transitions from admission to treatment outcome, treatment outcome to contact with CJS, and admission to contact with CJS (not completing treatment) for patients with and without PSU (Figure 2).

    Multistate scheme

    Figure 2: Multistate scheme

    We calculated the Aalen-Johansen for transition probabilities at 6 months, 1, 3 & 5 years\(^{[17]}\). Markdowns: https://fondecytacc.github.io/nDP/index_prop_grant23_24

Preliminary Results

  • Before IPWs, patients with PSU had lower incidence rates of treatment completion vs. patients with no PSU (IRR=0.53 95%CI: 0.51,0.54).
  • However, patients with PSU had greater rates of contact with the CJS vs. patients with no PSU (IRR=1.68 95%CI: 1.62,1.74).
  • After IPWs, patients with PSU still had lower rates of treatment completion vs. patients with no PSU (IRR=0.77 95%CI: 0.74,0.8)
  • Patients with PSU also had greater rates of contact with the CJS vs. patients with no PSU (IRR=1.11 95%CI: 1.06,1.17).
Table 1: Transition probabilities in states
Transition Time PSU No PSU
From admission to contact with CJS 6_mths 2.2 (2.1,2.3) 1.8 (1.7,1.9)
From admission to contact with CJS 1_yr 7.9 (7.6,8.1) 6.6 (6.4,6.8)
From admission to contact with CJS 3_yrs 24.4 (24.0,24.7) 20.7 (20.3,21.1)
From admission to contact with CJS 5_yrs 33.3 (32.8,33.7) 29.5 (29.0,30.0)
From admission to tr.completion 6_mths 3.1 (2.9,3.2) 4.0 (3.9,4.2)
From admission to tr.completion 1_yr 14.6 (14.3,14.8) 17.6 (17.3,18.0)
From admission to tr.completion 3_yrs 23.6 (23.2,23.9) 27.0 (26.6,27.4)
From admission to tr.completion 5_yrs 21.4 (21.0,21.8) 24.9 (24.4,25.3)
From tr.completion to contact with CJS 6_mths 3.0 (2.0,4.0) 2.4 (1.3,3.4)
From tr.completion to contact with CJS 1_yr 8.7 (7.5,9.8) 5.9 (4.8,7.0)
From tr.completion to contact with CJS 3_yrs 21.1 (20.0,22.3) 16.2 (15.1,17.3)
From tr.completion to contact with CJS 5_yrs 28.6 (27.4,29.8) 23.0 (21.8,24.2)

Transition probabilities: People with PSU have higher probabilities of contact with the CJS, both post-admission and post-treatment, vs. those without PSU. Similarly, they are less likely to complete treatment. Treatment completers had lower probabilities of CJS contact vs. non-completers after 3 years since admission (Table 1).

Discussion

Treatment completion can reduce the risk of criminal justice involvement, evident at the 3-year point when most users have finished treatment. Further analysis is needed. People with PSU may need enhanced treatment to complete treatments and avoid contact with the CJS.

References

[1] A. A. Duke et al. “Alcohol, drugs, and violence: A meta-meta-analysis.”. In: Psychology of Violence 8.2 (mar.. 2018), pp. 238-249. ISSN: 2152-081X. DOI: 10.1037/vio0000106.

[2] N. F. Sugie et al. “Beyond Incarceration: Criminal Justice Contact and Mental Health”. In: American Sociological Review 82.4 (ago.. 2017), pp. 719-743. ISSN: 0003-1224. DOI: 10.1177/0003122417713188.

[3] E. G. Thomas et al. “Association between contact with mental health and substance use services and reincarceration after release from prison”. In: PLOS ONE 17.9 (sept.. 2022), p. e0272870. ISSN: 1932-6203. DOI: 10.1371/journal.pone.0272870.

[4] A. N. Hassan et al. “Polydrug use disorders in individuals with opioid use disorder”. In: Drug and Alcohol Dependence 198 (may.. 2019), pp. 28-33. ISSN: 03768716. DOI: 10.1016/j.drugalcdep.2019.01.031.

[5] L. Wang et al. “Polydrug use and its association with drug treatment outcomes among primary heroin, methamphetamine, and cocaine users”. In: International Journal of Drug Policy 49 (nov.. 2017), pp. 32-40. ISSN: 09553959. DOI: 10.1016/j.drugpo.2017.07.009.

[6] J. A. Ford et al. “Types of criminal legal system exposure and polysubstance use: Prevalence and correlates among U.S. adults in the National Survey on Drug Use and Health, 2015–2019”. In: Drug and Alcohol Dependence 237 (ago.. 2022), p. 109511. ISSN: 03768716. DOI: 10.1016/j.drugalcdep.2022.109511.

[7] H. W. Andersson et al. “Relapse after inpatient substance use treatment: A prospective cohort study among users of illicit substances”. In: Addictive Behaviors 90 (mar.. 2019), pp. 222-228. ISSN: 03064603. DOI: 10.1016/j.addbeh.2018.11.008.

[8] C. Timko et al. “Systematic Review of Criminal and Legal Involvement After Substance Use and Mental Health Treatment Among Veterans: Building Toward Needed Research”. In: Substance Abuse: Research and Treatment 14 (ene.. 2020), p. 117822181990128. ISSN: 1178-2218. DOI: 10.1177/1178221819901281.

[9] J. Levola et al. “Psychosocial difficulties and treatment retention in inpatient detoxification programmes”. In: Nordic Studies on Alcohol and Drugs 38.5 (oct.. 2021), pp. 434-449. ISSN: 1455-0725. DOI: 10.1177/14550725211021263.

[10] H. W. Andersson et al. “Emerging Adults in Inpatient Substance Use Treatment: A Prospective Cohort Study of Patient Characteristics and Treatment Outcomes.”. In: European addiction research 27.3 (2021), pp. 206-215. ISSN: 1421-9891. DOI: 10.1159/000512156.

[11] H. W. Andersson et al. “Predictors of Dropout From Inpatient Substance Use Treatment: A Prospective Cohort Study”. In: Substance Abuse: Research and Treatment 12 (ene.. 2018), p. 117822181876055. ISSN: 1178-2218. DOI: 10.1177/1178221818760551.

[12] D. Basu et al. “Initial treatment dropout in patients with substance use disorders attending a tertiary care de-addiction centre in north India”. In: Indian Journal of Medical Research 146.8 (2017), p. 77. ISSN: 0971-5916. DOI: 10.4103/ijmr.IJMR_1309_15.

[13] J. C. Reyes et al. “Prevalence and Patterns of Polydrug Use in Latin America: Analysis of Population-based Surveys in Six Countries”. In: Review of European Studies 5.1 (feb.. 2013). ISSN: 1918-7181. DOI: 10.5539/res.v5n1p10.

[14] R. Santis B et al. “Consumo de sustancias y conductas de riesgo en consumidores de pasta base de caca'ina no consultantes a servicios de rehabilitación”. In: Revista médica de Chile 135.1 (ene.. 2007). ISSN: 0034-9887. DOI: 10.4067/S0034-98872007000100007.

[15] C. F. Olivari et al. “Polydrug Use and Co-occurring Substance Use Disorders in a Respondent Driven Sampling of Cocaine Base Paste Users in Santiago, Chile”. In: Journal of Psychoactive Drugs 54.4 (ago.. 2022), pp. 348-357. ISSN: 0279-1072. DOI: 10.1080/02791072.2021.1976886.

[16] S. R. Cole et al. “Constructing Inverse Probability Weights for Marginal Structural Models”. In: American Journal of Epidemiology 168.6 (jul.. 2008), pp. 656-664. ISSN: 0002-9262. DOI: 10.1093/aje/kwn164.

[17] M. J. Crowther et al. MULTISTATE: Stata module to perform multi-state survival analysis. ene.. 2023. <URL: https://econpapers.repec.org/RePEc:boc:bocode:s458207>.

Funding sources: This work was funded by ANID -Millennium Science Initiative Program- N° NCS2021_003 (Castillo-Carniglia) and N° NCS2021_013 (Calvo); The authors have no conflict of interest to declare